Skip to main content
To refer to this page use:
Full metadata record
DC FieldValueLanguage
dc.contributor.authorAmiri, Mohammad Mohammadi-
dc.contributor.authorDuman, Tolga M-
dc.contributor.authorGunduz, Deniz-
dc.contributor.authorKulkarni, Sanjeev R-
dc.contributor.authorPoor, H Vincent Poor-
dc.identifier.citationAmiri, Mohammad Mohammadi, Duman, Tolga M, Gunduz, Deniz, Kulkarni, Sanjeev R, Poor, H Vincent Poor. (2021). Blind Federated Edge Learning. IEEE Transactions on Wireless Communications, 20 (8), 5129 - 5143. doi:10.1109/twc.2021.3065920en_US
dc.description.abstractWe study federated edge learning (FEEL), where wireless edge devices, each with its own dataset, learn a global model collaboratively with the help of a wireless access point acting as the parameter server (PS). At each iteration, wireless devices perform local updates using their local data and the most recent global model received from the PS, and send their local updates to the PS over a wireless fading multiple access channel (MAC). The PS then updates the global model according to the signal received over the wireless MAC, and shares it with the devices. Motivated by the additive nature of the wireless MAC, we propose an analog `over-the-air' aggregation scheme, in which the devices transmit their local updates in an uncoded fashion. However, unlike recent literature on over-the-air FEEL, here we assume that the devices do not have channel state information (CSI), while the PS has imperfect CSI. On the other hand, the PS is equipped with multiple antennas to alleviate the destructive effect of the channel, exacerbated due to the lack of perfect CSI. We design a receive beamforming scheme at the PS, and show that it can compensate for the lack of perfect CSI when the PS has a sufficient number of antennas. We also derive the convergence rate of the proposed algorithm highlighting the impact of the lack of perfect CSI, as well as the number of PS antennas. Both the experimental results and the convergence analysis illustrate the performance improvement of the proposed algorithm with the number of PS antennas, where the wireless fading MAC becomes deterministic despite the lack of perfect CSI when the PS has a sufficiently large number of antennas.en_US
dc.format.extent5129 - 5143en_US
dc.relation.ispartofIEEE Transactions on Wireless Communicationsen_US
dc.rightsAuthor's manuscripten_US
dc.titleBlind Federated Edge Learningen_US
dc.typeJournal Articleen_US

Files in This Item:
File Description SizeFormat 
2010.10030.pdf463.42 kBAdobe PDFView/Download

Items in OAR@Princeton are protected by copyright, with all rights reserved, unless otherwise indicated.